An improved understanding of dopamine signaling patterns in the brain's reward processing systems will lead to mechanistic descriptions of reward-related behavior, and also to the discovery of new biomarkers and therapeutic intervention points for treatment of addiction. Here we propose to use a unique new molecular-level functional brain imaging technique to characterize dopamine signaling evoked by some of the most widely studied and broadly significant stimuli in addiction research. The technique uses magnetic resonance imaging (MRI) in conjunction with contrast agents that bind and report dopamine concentrations, reversibly, as a function of time.
In Specific Aim 1, we will use this molecular fMRI technique to map the structure and dynamics of dopamine release patterns in the striatum, a key target of dopamine signaling related to reward and addiction. We will measure dopamine release in response to an important addictive drug, amphetamine, as well as to reward-related brain stimulation. We will also push the spatial coverage and resolution of the imaging itself in order to characterize details of the dopamine response, such as specificity to anatomically and neurochemically defined striatal subregions, and we will for the first time conduct dopamine MRI studies in awake animals. Data will be obtained at a spatial resolution of 100-200 m and over temporal scales ranging from seconds to minutes, sufficient for resolving both phasic and longer-lasting dopamine changes.
In Specific Aim 2, we will establish a quantitative, spatially-resolved correspondence between molecular fMRI readings and conventional hemodynamic fMRI signals, which broadly reflect neuronal population activi- ty. These experiments will provide an empirical description of the relationship between BOLD signal and dopamine release, and also facilitate circuit level description of dopaminergic function at a neural population level across the striatum and beyond.
In Specific Aim 3, we propose to develop an alternative MRI sensor that will detect dopamine concentrations of 0.1-1 M, 10-100 times better than our current sensors, and in the range of levels evoked by naturalistic rewarding stimuli. The improved sensors will be formed from na- noscale arrays of magnetic particles that change configuration in the presence of target ligands, bringing about MRI contrast changes. In additional to enabling sensitive dopamine detection, the new design will in the future be generalizable to other neural targets.
These Aims will have broad impact on the study of do- paminergic neural systems important in addiction, and will also address goals of the federal BRAIN Initiative.

Public Health Relevance

We propose to use a novel molecular-level brain imaging technique to help understand how the neurotransmitter dopamine signals during stimuli related to addiction. By comparing molecular imaging results to traditional functional magnetic resonance imaging (fMRI), we will learn how to interpret human fMRI results in the striatum in terms of dopamine signaling; we will also develop a new type of sensor that will make dopamine imaging considerably more sensitive. These steps will promote the understanding of addiction in animal models and possibly lead to improvements in the diagnosis or treatment of addiction- related disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Research Project (R01)
Project #
1R01DA038642-01A1
Application #
8963489
Study Section
Neurobiology of Motivated Behavior Study Section (NMB)
Program Officer
Pariyadath, Vani
Project Start
2015-08-15
Project End
2020-06-30
Budget Start
2015-08-15
Budget End
2016-06-30
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Massachusetts Institute of Technology
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
001425594
City
Cambridge
State
MA
Country
United States
Zip Code
Ghosh, Souparno; Harvey, Peter; Simon, Jacob C et al. (2018) Probing the brain with molecular fMRI. Curr Opin Neurobiol 50:201-210
Okada, Satoshi; Bartelle, Benjamin B; Li, Nan et al. (2018) Calcium-dependent molecular fMRI using a magnetic nanosensor. Nat Nanotechnol 13:473-477
Fiallos, Ana M; Bricault, Sarah J; Cai, Lili X et al. (2017) Reward magnitude tracking by neural populations in ventral striatum. Neuroimage 146:1003-1015
Hai, Aviad; Cai, Lili X; Lee, Taekwan et al. (2016) Molecular fMRI of Serotonin Transport. Neuron 92:754-765